1. Field of the Invention
The present invention generally relates to data transmission systems, such as those used in computer and telecommunications networks, and particularly to fiber optic transmission systems for high-speed digital traffic, such as synchronous optical network (SONET) systems. More specifically, the present invention is directed to an improved method and apparatus for providing error correction in a SONET transmission system.
2. Description of the Related Art
As information technology progresses, increasingly difficult demands are being placed on data transmission systems that support the transfer of information between computing devices. A variety of computer and telecommunications networks have been devised to handle the growing traffic in data, voice and video signals. Typical network designs include local area networks (LANs), ring-connected networks such as token ring, integrated services digital networks (ISDNs), and wide area networks (WANs) such as system network architecture (SNA) networks, or packet (X.25) networks (including the Internet). Various protocols are used to manage the transmission of information between clients and servers (or peers) in these networks, using intelligent agents located at network nodes, routers and bridges.
One of the key requirements of a high-speed digital network is to reduce the end-to-end delay in order to satisfy real-time delivery constraints, and to achieve the necessary high nodal throughput for the transport of voice and video. Given the growing number of network interconnections, more advanced distributed processing capabilities between workstations and supercomputers, and the pervasive use of the Internet, the current data transmission profile requires ever more bandwidth and connectivity. Although copper wires have been the preferred transmission media for decades, the physical limitations imposed by copper lines have forced the communications industry to rely more heavily on fiber-optic transmission systems. One such system is commonly referred to as a synchronous optical network (SONET).
SONET is an intelligent system that provides advanced network management with a standard optical interface. The American National Standards Institute (ANSI) coordinates and approves SONET standards. An international version of SONET known as synchronous digital hierarchy (SDH) is published by the International Telecommunications Union (ITU). In a WAN or over the Internet, data traffic is often carried over SONET lines, sometimes using asynchronous transfer mode (ATM) technology as a management layer. SONET uses octet multiplexing to create a higher-speed data stream from lower-speed tributary signals. A signal hierarchy referred to as synchronous transport signals (STS) is used to aggregate lower speed lines. For example, the synchronous transport signal level 1 (STS-1) electrical circuits are used to support the corresponding SONET optical carrier 1 (OC-1) optical signals with a basic speed of 51.84 Mbits/s. Higher STS levels (STS-n) provide speeds that are multiples of STS-1, and are created by interleaving STS-1 signals, octet-by-octet. Synchronous transport signals are divided into a fixed number of frames of 125 μs duration.
SONET uses a self-healing ring architecture that allows traffic to be rerouted if one communications path is disabled. A typical SONET ring comprises a plurality of hubs or nodes, each coupled to another by at least one optical fiber link. At each node, a gateway converts an incoming electrical signal that may be associated with a telephone call into a block of optical information. The gateway places the block of optical information onto the ring within a particular time slot of an interchange frame having a particular synchronization (speed). Each time slot in each frame corresponds to a particular destination (i.e., node) within the ring. Thus, the gateway at each node converts the block of information appearing within the time slot associated with that node into corresponding electrical signals. In this way, traffic on the ring is routed in automatically. Connecting a large number of nodes (i.e., gateways) in a single ring is often impractical, so some nodes may be organized into smaller (subsidiary) rings that are connected to each other by a backbone ring to minimize the length of the fiber links. SONET backbones are widely used to aggregate T1 and T3 lines (lines that use T-carrier multiplexing).
SONET offers bandwidth up to OC-192 (9.953 Gbits/s) and can carry a wide variety of information. SONET also offers exceptional BERs (bit-error rates) of, e.g., 1 error in 10 billion bits, compared with copper transmission methods of 1 error in 1 million bits. Error detection and correction is an essential aspect of any SONET system. Data may be corrupted during transmission due to many different reasons, such as a soft error (a random, transient condition caused by, e.g., stray radiation, electrostatic discharge, or excessive noise), or a hard error (a permanent condition, e.g., a defective circuit or memory cell). One common cause of errors is a soft error resulting from alpha radiation emitted by the lead in the solder (C4) bumps used to form wire bonds with circuit leads. Most errors are single-bit errors, that is, only one bit in the field is incorrect.
Two primary error control strategies have been popular in practice. They are the FEC (Forward Error Correction) strategy, which uses error correction alone, and the ARQ (Automatic Repeat Request) strategy which uses error detection combined with retransmission of corrupted data. The ARQ strategy is generally preferred for several reasons. The main reason is that the number of overhead bits needed to implement an error detection scheme is much less then the number of bits needed to correct the same error. ARQ algorithms include cyclical redundancy check (CRC) codes, serial parity, block parity, and modulo checksum. Parity checks, in their most simple form, constitute an extra bit that is appended to a binary value when it is to be transmitted to another component. The extra bit represents the binary modulus (i.e., 0 or 1) of the sum of all bits in the binary value. In this manner, if one bit in the value has been corrupted, the binary modulus of the sum will not match the setting of the parity bit. If, however, two bits have been corrupted, then the parity bit will match, falsely indicating a correct parity. In other words, a simple parity check will detect only an odd number of incorrect bits (including the parity bit itself).
The FEC strategy is mainly used in links where retransmission is impossible or impractical, and is usually implemented in the physical layer, transparent to upper layers of the transmission protocol. When the FEC strategy is used, the transmitter sends redundant information along with the original bits, and the receiver decodes the bits to identify and correct errors. The number of redundant bits in FEC is much larger than in ARQ. However, several factors have provided the impetus for reconsideration of the traditional preference for retransmission schemes over forward error correction techniques. Those factors include the increased speed and decreased price of processors, and the emergence of certain applications for which retransmission for error recovery is undesirable or impractical. For example, some video applications by their very nature exclude the possibility of using data retransmission schemes for error recovery. Another application in which data retransmission schemes appear ill-suited for implementation is wireless data communications systems. Those systems are known for their high number of retransmissions necessitated by various sources of random noise and deterministic interference that give rise to corrupted receptions. The significant number of retransmissions on those wireless channels may be cost-prohibitive when one considers the relatively high cost of bandwidth for wireless data connections.
Algorithms used for FEC include convolutional codes, Hamming codes, Reed-Solomon codes, and BCH (Bose-Chaudhuri-Hocquenghem) codes. BCH codes form a large class of powerful random error-correcting cyclic codes, and have the advantage of being robust and very efficient in terms of the relatively low number of check bits required. These check bits are also easily accommodated in the unused SONET overhead byte locations. BCH codes are specified with three primary parameters, n, k, and t, where:                n=block length (the length of the message bits plus the additional check bits)        k=message length (the number of data bits included in a check block)        t=correctable errors (the number of errors per block which the code can correct).BCH codes have the property that the block length n is equal to 2m−1, where m is a positive integer. The code parameters are denoted as (n,k). Another parameter often referred to is the “minimum distance” dmin≧2t+1. The minimum distance defines the minimum number of bit positions by which any two code words can differ. A hybrid FEC/ARQ technique which utilizes BCH coding is disclosed in U.S. Pat. No. 5,844,918. The ITU committee responsible for error correction in SONET networks (committee T1X1.5) has developed a standard for FEC in SONET OC-192 systems which implements a triple-error correcting BCH code referred to as BCH-3.        
Galois field mathematics is the foundation for BCH-based forward error correction. A Galois field is a type of field extension obtained from considering the coefficients and roots of a given polynomial (also known as root field). The generator polynomial for a t-error correcting BCH code is specified in terms of its roots from the Galois field GF(2m). If α represents the primitive element in GF(2m), then the generator polynomial g(X) for a t-error correcting BCH code of length 2m−1 is the lowest-degree polynomial which has α, α2, α3, . . . , α2t as its roots, i.e., g(αi)=0 for 1≦i≦2t. It can be shown from the foregoing that g(X) must be the least common multiple (LCM) of φ1(X), φ3(X), . . . , φ2t−1(X), where φi(X) is the minimal polynomial of αi. For example, the triple-error correcting BCH code of length 15 is generated by the polynomial                               g          ⁡                      (            X            )                          =                ⁢                  LCM          ⁢                      {                                                            φ                  1                                ⁡                                  (                  X                  )                                            ,                                                φ                  3                                ⁡                                  (                  X                  )                                            ,                                                φ                  5                                ⁡                                  (                  X                  )                                                      }                                                  =                ⁢                              (                          1              +              X              +                              X                4                                      )                    ⁢                      (                          1              +              X              +                              X                2                            +                              X                3                            +                              X                4                                      )                    ⁢                      (                          1              +              X              +                              X                2                                      )                                                  =                ⁢                  1          +          X          +                      X            2                    +                      X            4                    +                      X            5                    +                      X            8                    +                                    X              10                        .                              A more detailed discussion of Galois mathematics as applied to BCH codes may be found in chapter 6 of “Error Control Coding: Fundamentals and Applications,” by Shu Lin and Daniel J. Costello, pp. 141-170.
Decoding of BCH codes likewise requires computations using Galois field arithmetic. Galois field arithmetic can be implemented (in either hardware or software) more easily that ordinary arithmetic because there are no carry operations. The first step in decoding a t-error correction BCH code is to compute the 2t syndrome components S1, S1, . . . , S2t. For a hardware implementation, these syndrome components may be computed with feedback registers that act as a multiply accumulator (MAC). Since the generator polynomial is a product of, at most, t minimal polynomials, it follows that, at most, t feedback shift registers (each consisting of at most m stages) are needed to form the 2t syndrome components, and it takes n clock cycles to complete those computations. It is also necessary to find the error-location polynomial which involves roughly 2t2 additions and 2t2 multiplications. Finally, it is necessary to correct the error(s) which, in the worst case (for a hardware implementation), requires t multipliers shifted n times. Accordingly, circuits that implement BCH codes are typically either quite complex, or require many operations. For example, the BCH-3 iterative algorithm requires up to five separate steps, with each step involving a varying number of computations, and any hardware implementation of BCH-3 must support the maximum possible number of steps/computations.
In light of the foregoing, it would be desirable to devise an improved hardware implementation for BCH decoding that reduces the number of steps/computations required for the decoding algorithm. In particular, it would be desirable to devise a Galois field multiply accumulator that performs the multiply/accumulate operations faster. It would be further advantageous if the decoder could be provided with a means to verify the correct operation of the FEC circuitry.